teaching
ETH Zurich advocates a proactive approach to the use of generative AI in educational contexts, emphasising responsible use among students and lecturers.
Review: Agent reviewed
Change log
ETH Zurich
Release-to-release tracker diff with separate policy-text, newly-extracted claim, evidence, and source snapshot categories.
Change summary
Current public record freshness and review state.
ETH Zurich currently has 8 source-backed claim records and 5 official source attributions. Latest tracked changed date: May 5, 2026. No tracker diff rows are recorded in the latest public release.
This tracker is not legal advice, not academic integrity advice, and not an official university statement unless a linked source is the university's own official page.
Newly extracted claims are tracker additions and are not necessarily newly published by the university. Source snapshot changes show hash changes for the same source URL and are not by themselves policy changes.
Diff categories
Semantic classification for this release diff.
Release diff
Unified tracker diff generated from the previous and current public release snapshots.
No tracker claim/evidence/source changes are recorded for this university in the latest public release.
Claim changes
8 claim records
academic_integrity
Students are responsible for the content of work they submit. Performance assessments must be conducted independently and personally; GenAI may serve a supplementary role but not replace student efforts.
Review: Agent reviewed
teaching
Lecturers determine whether and how GenAI may be used in their courses and for respective assessments. Teaching materials created with GenAI must be subjected to quality control by the lecturer.
Review: Agent reviewed
academic_integrity
Violations of GenAI guidelines such as use of unauthorised aids or non-disclosure of their use are subject to disciplinary action under existing performance assessment rules and the declaration of originality.
Review: Agent reviewed
ai_tool_treatment
ETH Zurich recommends Microsoft Copilot, Google Gemini, and NotebookLM for teaching purposes, as they offer data-protected access via ETH accounts where personal data is not used for training models.
Review: Agent reviewed
privacy
Students must refrain from disclosing copyrighted, private, or confidential information to commercial GenAI clients unless expressly permitted, and must respect privacy and copyright of content they work with.
Review: Agent reviewed
teaching
ETH Zurich requires transparency about GenAI use: students must declare which tools they used and for which parts of their work; lecturers must communicate when GenAI use is permitted and make their own GenAI use visible.
Review: Agent reviewed
academic_integrity
ETH Zurich states that technical recognition of AI-generated output is currently unreliable and will probably remain so; trust in such methods is not appropriate.
Review: Agent reviewed
Source snapshots
5 source attributions
Academic Integrity | ETH Zurich
official_guidance Tracker checked at May 5, 2026, 5:43 PM
AI in Teaching and Learning — ETH Zurich
official_guidance Tracker checked at May 5, 2026, 5:43 PM
AI Tools & Licenses | ETH Zurich
official_guidance Tracker checked at May 5, 2026, 5:43 PM
ETH AI Ethics Policy Network
official_guidance Tracker checked at May 5, 2026, 5:43 PM
Generative AI in Teaching and Learning — Guidelines (ETH Zurich)
official_policy_page Tracker checked at May 5, 2026, 5:43 PM